The SaasRise Mastermind meetings on September 16, 2026 featured discussions among SaaS CEOs and founders on these topics.
This is what we discussed today in the Enterprise SaaS CEO and Founder Mastermind
This week's SaasRise discussions covered how SaaS leaders are extracting real business value from AI without over-engineering it, from anonymized case studies and company knowledge bases to handing legacy codebases over to Claude. The conversations also focused on rebuilding outbound and search visibility as volume tactics lose effectiveness, and on capital decisions: finding the right investors, balancing a cash-cow product against an AI-first bet, preparing for an exit, and choosing where to manufacture hardware.
September 17, 2026
The top M&A deals, venture deals, news, and blog posts of the week
Most SaaS homepages still lean on the old lead-magnet playbook, a form full of fields standing between a visitor and your product. Here's why that habit is quietly costing you signups, and what to put there instead.
AI makes it possible to generate a personalized asset for every prospect on your list, but the economics only work if you're smart about what you generate and when. Here's the two-step approach that makes AI-personalized outbound actually pencil out on low-dollar deals.
A practical walkthrough for B2B SaaS teams on how to turn a target account list into a clean ABM leads list using Clay, Apollo, Instantly, and ListKit, then dedupe, segment, and use it across outbound, LinkedIn, and matched audience ads.
A practical guide for SaaS founders and product leaders on using Claude Code to strengthen testing, QA, code review, and release processes so teams can ship faster without increasing regressions or production risk.
A practical guide for SaaS founders and product leaders on how to use Claude Code to safely modernize an existing SaaS application, reduce technical debt, improve AI-readiness, and unlock faster product development without creating regressions.
A founder-focused guide to using Claude Code to understand, map, and safely improve existing codebases. It explains how AI can help product and engineering teams read complex repositories, plan changes before editing, connect prototypes to real systems, and move faster without losing technical discipline.
